An agonist-antagonist myoneural interface for proprioception from a neurally-controlled prosthesis

Abstract

Humans have the ability to precisely sense the position, speed, and torque of their body parts. This sense is known as proprioception, and is essential to human motor control. In the many attempts to create human-mechatronic interactions, there is still no robust, repeatable methodology to reflect proprioceptive information from a synthetic device onto the nervous system. As a solution to this shortcoming, I present the agonist-antagonist myoneural interface (AMI). The AMI is comprised of 1) a surgical construct made up of two muscle-tendons - an agonist and an antagonist - surgically connected in series so that contraction of one muscle stretches the other, and 2) a bi-directional efferent-afferent neural control architecture. The AMI preserves dynamic muscle relationships that exist within native anatomy, thereby allowing proprioceptive signals from biological sensors within both muscles to be communicated to the central nervous system. Each AMI is designed to send control signals to one joint of a prosthesis, and to provide proprioceptive feedback pertaining to the movement of that joint. The doctoral work presented in this thesis constitutes the pre-clinical and early clinical validation of the AMI. The AMI concept is first described and validated in small (murine) and large (caprine) pre-clinical models. A detailed surgical methodology for implementation of the AMI during primary below-knee amputation is then described and evaluated in three human patients. Characterization of independent neural control of prosthetic joint position and impedance is presented for one AMI patient, as compared to a group of four persons with traditional amputation. Data are shown evidencing improved volitional control over the prosthesis in the AMI patient, as well as an emergence of natural reflexive behaviors during stair ambulation that do not exist in the traditional amputation cohort. These results provide a framework for reconsidering the integration of bionic systems with human physiology.